Data reveals what happened, but not why. In this article, I explore the limits of analytics and how product teams can uncover deeper insights through session replays, user interviews, support tickets, and hands-on empathy. The real breakthroughs come when we blend data with human context - and start building for people, not just metrics.
We live in a world obsessed with metrics. Clicks, conversions, churn, CAC, LTV, DAUs — dashboards lit up like Time Square and every product conversation starts (and sometimes ends) with the numbers. Don’t get me wrong - I love data. It’s essential. But if there’s one thing I’ve learned after running dozens of A/B tests and growth experiments, it’s this:
Data tells you what happened. It doesn’t tell you why.
And often, that “why” is where the real insight lives.
Imagine this: your product’s onboarding funnel suddenly tanks. Step 3, previously solid, now shows a sharp drop-off. Naturally, you dive into the analytics - segmentation, device types, time of day, anything that might explain the dip. Maybe you A/B test a few copy changes or tweak the UI spacing.
Still no lift.
Now what?
Here’s where most teams stall. They keep poking at the numbers, hoping a hidden variable will reveal itself. But numbers, no matter how granular, don’t speak human. They don’t tell you that users felt uncertain, or overwhelmed, or just plain confused. They don’t show hesitation in someone’s eyes, or the half-second pause before they abandon the flow. But if you start looking beyond the metrics, you might just start to see things differently.
When the data doesn’t give me enough, here’s where I go next:
Tools like FullStory, Hotjar, or LogRocket give you a front-row seat to real user behaviour. You’ll see users hesitate before clicking a button, rage-clicking in frustration, or scrolling back and forth like they’re lost. These micro-moments expose friction that data alone can’t.
Customer support is a goldmine of unsurfaced insights. Reading through tickets reveals the language users actually use - what confused them, what they expected, and how they felt. Patterns emerge fast when you stop scanning for complaints and start looking for context.
This is the hardest but most rewarding step. Just talking to 3 - 5 users can uncover motivations and mental models no funnel analysis ever will. Ask open-ended questions. Watch how people describe your product. Most importantly, don’t pitch or defend - just listen.
Sometimes the issue isn’t user confusion - it’s just poor UX. Walk through the journey yourself. Ask: if I’d never seen this before, would I know what to do? What assumptions am I making as a product insider that my users might not share?
The best product teams don’t treat data as gospel - they treat it as a signal. It starts the conversation, but it rarely ends it. The real breakthroughs happen when you zoom out, bring in human context, and reconnect with the people behind the pixels.
Some of my most meaningful product changes didn’t come from a dashboard. They came from watching a user get stuck and hearing them say, “I wasn’t sure what this button did, so I just left.” That sentence told me more than any retention chart ever could.
Data is incredibly powerful - but it has limits. It can tell you that something’s broken, but not how to fix it. It shows the “what,” but not the “why.”
To find the why:
In the end, great product decisions don’t just balance intuition with evidence — they blend analytics with empathy.
Data starts the conversation, empathy finishes it.
That’s how you stop optimising for metrics and start building for people.
If you’re building something ambitious, I’d love to be part of it. Reach out to chat about your next product or growth challenge.
